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ARS Home » Southeast Area » Stoneville, Mississippi » Genomics and Bioinformatics Research » Research » Publications at this Location » Publication #326640
Title: Evaluation of carbon nanotube based copper nanoparticle composite for the efficient detection of agroviruses

Author
item TAHIR, MUHAMMAD - National Institute Of Biotechnology And Genetic Engineering (NIBGE)
item BAJWA, SADIA - National Institute Of Biotechnology And Genetic Engineering (NIBGE)
item MANSOOR, SHAHID - National Institute Of Biotechnology And Genetic Engineering (NIBGE)
item BRIDDON, ROB - National Institute Of Biotechnology And Genetic Engineering (NIBGE)
item KHAN, WAHEED - National Institute Of Biotechnology And Genetic Engineering (NIBGE)
item Scheffler, Brian
item AMIN, IMRAN - National Institute Of Biotechnology And Genetic Engineering (NIBGE)

Submitted to: Journal of Hazardous Materials
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/9/2017
Publication Date: 3/15/2018
Publication URL: https://handle.nal.usda.gov/10113/5922755
Citation: Tahir, M.A., Bajwa, S.Z., Mansoor, S., Briddon, R.W., Khan, W.S., Scheffler, B.E., Amin, I. 2018. Evaluation of carbon nanotube based copper nanoparticle composite for the efficient detection of agroviruses. Journal of Hazardous Materials. 346:27–35. doi: 10.1016/j.jhazmat.2017.12.007.
DOI: https://doi.org/10.1016/j.jhazmat.2017.12.007

Interpretive Summary: Rapid and precise identification of pathogens is a challenge to agricultural production. Often farmers or consultants are limited to physically characterizing symptoms of an infected plant when making a judgement of what is impacting the crops. In many instances this means new strains of pathogens are not detected early on or the plant symptoms could be attributed to several different pathogens. Naturally samples can be tested for certain pathogens by various means but often this means a sample must be submitted to a qualified lab and this test can be expensive or time consuming. For some pathogens, there are relatively inexpensive antibody “dipstick” methods but they might not detect strain variation. This manuscript is based on the development and validation of a nano-biosensor for the detection of DNA from a cotton leaf curl virus. This method has the potential to a be a rapid and inexpensive method for the detection of this virus. As the method is based on the viral DNA sequence, it means the probe detecting this sequence can be changed to identify specific strains. Further modifications of this system could result in a system directly suitable for use in the field.

Technical Abstract: Nanomaterials based sensors offer sensitivity and selectivity for the detection of a specific analyte-of-the-interest. Described here is a novel assay for the detection of a DNA sequence based on nanostructured carbon nanotubes/copper nanoparticles composite. This assay was modeled on strong electrostatic interactions between a positively charged composite and a negatively charged target DNA specific to Cotton leaf curl Khokhran virus-Burewala strain (CLCuKoV-Bur) via covalent attachment. The hybridization sequences were studied by monitoring cyclic voltammetry and differential pulse voltammetry signals in the presence of test probe strands. The designed composite was characterized by scanning electron microscope and atomic force microscopy showing that the diameter of nanotubes and particles was nearly 50-100 nm and 20-100 nm, respectively. After exposure to complementary DNA, sensor signals of the capture probe decreased from 7 x 10-4 A to 1 x 10-4 A due to hybridization. But in the case of non-complimentary DNA (GroEl Gene), insignificant decrease in signals was observed from 7 x 10-4 A to 6.8 x 10-4 A. This sensor was tested for the detection of CLCuKoV-Bur and it was observed that it can detect up to 10 x 10-14 gm concentrations. This DNA biosensor can be applied to infected leaf samples to detect CLCuKoV-Bur without performing DNA extractions and other time consuming techniques like PCR, or qPCR. This newly designed electrochemical DNA nano-biosensor offers a quick sensitive and selective detection of CLCuKoV-Bur that can be used for the detection of field infected samples.